The need for language translation has existed ever since there was the desire for communication as between different ethnic groups. Typically a local in person translator was used to translate either a live conversation on-the-fly or would translate text to text from one language to another language. The accuracy of this method depended greatly upon the skill and knowledge of the particular translator, as with many language translations, there is not a word for word correlation, thus the translator must translate thoughts, concepts, and ideas in conveying from the original language into the new language, therein lies the problem with automated software language systems—wherein the automated translation system puts forth some form of automated logic on a word for word basis, thus increasing the opportunity for error in the language translation. This of course leaves the opportunity for misinterpretation or lack of understanding in the translation, this can be especially troublesome when the translation work involves highly technical, scientific, or some specialized lexicon data in the language to be translated that either the automated language software has no automated logic for, resulting in an even higher number of errors, or the particular human manual translator may not be familiar with, in other words a translator may know several languages well, however, the translator may not be familiar with a specialized vocabulary applicable to a specific technical field which increases the opportunity for translation errors even when the language translation is done manually. As examples, for specialized lexicons in the legal, medical, scientific, technical, and similar fields are especially troublesome to get an accurate language translation easily, as the automated language translation software would be prone to a large number of errors and for the human manual language translator—they may not have the right skills to complete the desired language translation in a specialized lexicon with any degree of accuracy.
There are been numerous attempts to automate translation through software, which is very attractive for completing a high number of translations quickly and at low cost, however, due to the problems mentioned above of specialized terminology, i.e. the lexicon not being easily translated in an accurate manner, with automated translation this specialized terminology/accuracy problem is made even worse as the translation data bases currently have a hard time of interpreting context of the translated idea or thought, as by necessity the translation databases must use set logic which can work acceptably well in simple basic conversation type words to be translated, however, any translation being beyond this and moving toward a technical or specialized nature, the error rate in automated translation would be too high to be acceptable.
In looking at the prior art in the language translation area starting with U.S. Pat. No. 6,292,769 to Flanagan et al. disclosed is a system for the automated translation of speech having speech recognition software as input for spoken words in online chat or conferencing systems. Thus in Flanagan et al., users may speak rather than type their messages and hear comments from other users. The speech data in Flanagan et al., is translated into textual data and submitted to the online information service or computer network for processing, see. column 2, lines 20-22 and lines 27-31.
Continuing in the prior art translation area in U.S. Pat. No. 5,351,189 to Doi et al. disclosed is a machine translation system including separated side-by-side display of original and corresponding translated sentences, wherein scrolling can be done to roll through the side-by-side display of original and translated segments. The machine translation system in Doi et al., comprises a translation processor for translating an original sentence by accessing a dictionary to produce a translated sentence corresponding to the original sentence, see column 2, lines 34-39.
Next, in the language translation prior art area in U.S. Pat. No. 6,996,520 to Levin disclosed is a language translation system of electronic communications that automatically selects and deploys specialized dictionaries based upon context recognition and other factors. The system in Levin includes a machine translation component which can access a database of specialized dictionaries and deploy search agents to search the internet for complementary specialized translation dictionaries, see column 3, lines 21-28. Also, in the translation arts in U.S. Pat. No. 5,384,701 to Stentiford et al., disclosed is a language translation system for translating phrases from a first language into a second language comprising a store holding collections of phrases in the second language. Phrases input in Stentiford et al., are characterized on the basis of keywords, and the corresponding phrases in the second language are output in an effort to increase speed and accuracy of automated translation. Thus in Stentiford et al., being similar to the typical tourist language translation “phrase book” of commonly used phrases such as “where is the bathroom” or “how much does this cost” as being more useful for typical conversation than a word for word translation when trying to communicate with someone in a different language—thus reinforcing the idea that in language translation it requires an “interpretation” of the meaning of a group of words to a similar meaning in the translated language, lending emphasis to the problem of either the automated language software translator or the manual human translator capacity to do this word group “interpretation” into the new language.
Further to this in the language translation arts, in U.S. Pat. No. 4,953,088 to Suzuki et al. disclosed is a sentence translator with processing stage indicator. The translation apparatus in Suzuki et al., has a computer which analyzes the original language sentence and generates a target language sentence based on the analyzed original language sentence. Suzuki et al., attempts to refine the word-to-word automated translation scheme by ascertaining the translated word criterion of its verb, noun, adverb, adjective, plural, singular, tense, person, and the like, associated with the looked up words to translate, by further using a comparison to perform a syntactic (criterion relationship), semantic (coordination of criterion), and context (expression theme of the criterion) analysis for determining a best fit scenario relationship as between the translated words criterion, while indicating the continual status of the translation. Thus in Suzuki et al., there is an attempt to further refine the logic of the language translation software to improve the translation accuracy, and as this may be done for commonly used conversational words in major languages, there would not be much motivation to refine the language translation logic to this degree in uncommon specialized technical lexicons due to the smaller need for these language translations, thus the automated language software translation inaccuracy would still exist for specialized technical lexicon language translations.
There exists a need to provide an internet based language translation system that attempts to combine the best of both worlds being the automated software language translation systems and the skilled human manual language translation in a central system that can allocate as between automated and manual language translation to best fulfill the particular translation needs of the translation client. The ideal internet based language translation system would avail itself of a multitude of both automated software language systems and a multitude of skilled manual human language translators, thus resulting in optimizing the accuracy of the language translation by pulling together as many ways of accomplishing language translation as possible—to best serve the languages involved and the potential specialized nature of the lexicon involved. This could be accomplished via a password protected basic web-site to show some information about the Collaborative Translation System (CTS) system, its usage and links and other resources for identifying the product's core functionality, such as maintaining a list of translator logins. A further aspect in the CTS system is the translation console that is a major component of the system. The CTS system console demonstrates the translator and translator administrator experience to monitor and translate messages, by having two modes: A first translator mode: having translator login, translator skill set-termed settings, shows the experience for the translator of receiving messages from the queue, translating them and sending them back, and cumulative data on the particular translator performance. A second administrator mode would include: administrator login, CTS system overall operational statistics, and particular translation case statistics.